{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 疲惫的人"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![疲惫的人](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594228415037&di=45695a42f54408820d37e4ea77fe105b&imgtype=0&src=http%3A%2F%2Fpic90.huitu.com%2Fres%2F20161112%2F851091_20161112153830755040_1.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import Series, DataFrame\n",
    "import requests\n",
    "import pandas as pd"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 生气的人\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.062</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        性别    年龄      微笑      情绪\n",
       "值   Female  27.0   0.062     NaN\n",
       "阈值     NaN   NaN  50.000     NaN\n",
       "生气     NaN   NaN     NaN  99.924\n",
       "厌恶     NaN   NaN     NaN   0.001\n",
       "恐惧     NaN   NaN     NaN   0.003\n",
       "幸福     NaN   NaN     NaN   0.001\n",
       "中性     NaN   NaN     NaN   0.002\n",
       "悲伤     NaN   NaN     NaN   0.070\n",
       "惊喜     NaN   NaN     NaN   0.001"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"ED**************H2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YU**************svXO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1595081244294&di=90f5c969e28a524d091090e86815a985&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fq_70%2Cc_zoom%2Cw_640%2Fimages%2F20171104%2F4fc9dc3545aa4865bba2898226339f81.jpeg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'request_id': '1594219900,51c10a46-5812-4fe5-9f9d-37706998e87d',\n",
       " 'time_used': 120,\n",
       " 'faces': [{'face_token': '31b6c92f8ac02a1c2557498990ad3553',\n",
       "   'face_rectangle': {'top': 165, 'left': 485, 'width': 145, 'height': 145},\n",
       "   'attributes': {'gender': {'value': 'Male'},\n",
       "    'age': {'value': 30},\n",
       "    'smile': {'value': 0.517, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.188,\n",
       "     'disgust': 0.63,\n",
       "     'fear': 0.011,\n",
       "     'happiness': 0.589,\n",
       "     'neutral': 98.548,\n",
       "     'sadness': 0.024,\n",
       "     'surprise': 0.011}}}],\n",
       " 'image_id': 'y03fs3PCaPPKDfuU47Q77w==',\n",
       " 'face_num': 1}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"EDw**************H2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YUx**************vXO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594228415037&di=45695a42f54408820d37e4ea77fe105b&imgtype=0&src=http%3A%2F%2Fpic90.huitu.com%2Fres%2F20161112%2F851091_20161112153830755040_1.jpg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>Male</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.517</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>threshold</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>anger</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>disgust</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fear</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>happiness</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>neutral</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sadness</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>surprise</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             性别    年龄      微笑      情绪\n",
       "value      Male  30.0   0.517     NaN\n",
       "threshold   NaN   NaN  50.000     NaN\n",
       "anger       NaN   NaN     NaN   0.188\n",
       "disgust     NaN   NaN     NaN   0.630\n",
       "fear        NaN   NaN     NaN   0.011\n",
       "happiness   NaN   NaN     NaN   0.589\n",
       "neutral     NaN   NaN     NaN  98.548\n",
       "sadness     NaN   NaN     NaN   0.024\n",
       "surprise    NaN   NaN     NaN   0.011"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "pd.DataFrame(results['faces'][0]['attributes']).rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'face_token': '31b6c92f8ac02a1c2557498990ad3553',\n",
       "  'face_rectangle': {'top': 165, 'left': 485, 'width': 145, 'height': 145},\n",
       "  'attributes': {'gender': {'value': 'Male'},\n",
       "   'age': {'value': 30},\n",
       "   'smile': {'value': 0.517, 'threshold': 50.0},\n",
       "   'emotion': {'anger': 0.188,\n",
       "    'disgust': 0.63,\n",
       "    'fear': 0.011,\n",
       "    'happiness': 0.589,\n",
       "    'neutral': 98.548,\n",
       "    'sadness': 0.024,\n",
       "    'surprise': 0.011}}}]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results['faces']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'gender': {'value': 'Male'},\n",
       " 'age': {'value': 30},\n",
       " 'smile': {'value': 0.517, 'threshold': 50.0},\n",
       " 'emotion': {'anger': 0.188,\n",
       "  'disgust': 0.63,\n",
       "  'fear': 0.011,\n",
       "  'happiness': 0.589,\n",
       "  'neutral': 98.548,\n",
       "  'sadness': 0.024,\n",
       "  'surprise': 0.011}}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results['faces'][0]['attributes']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 疲劳的人\n",
    "![疲劳的人](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233726108&di=9201a88959f1ae37b37ea8101d855d5f&imgtype=0&src=http%3A%2F%2Ft8.baidu.com%2Fit%2Fu%3D4197399356%2C2330501341%26fm%3D193)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Female</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2.069</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79.564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.619</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        性别    年龄      微笑      情绪\n",
       "值   Female  24.0   2.069     NaN\n",
       "阈值     NaN   NaN  50.000     NaN\n",
       "生气     NaN   NaN     NaN   0.215\n",
       "厌恶     NaN   NaN     NaN   0.304\n",
       "恐惧     NaN   NaN     NaN   8.893\n",
       "幸福     NaN   NaN     NaN   0.271\n",
       "中性     NaN   NaN     NaN  79.564\n",
       "悲伤     NaN   NaN     NaN  10.135\n",
       "惊喜     NaN   NaN     NaN   0.619"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests\n",
    "\n",
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"EDw**************2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YUx**************vXO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233726108&di=9201a88959f1ae37b37ea8101d855d5f&imgtype=0&src=http%3A%2F%2Ft8.baidu.com%2Fit%2Fu%3D4197399356%2C2330501341%26fm%3D193\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 精神的人\n",
    "![未知](https://ss1.bdstatic.com/70cFuXSh_Q1YnxGkpoWK1HF6hhy/it/u=180314823,2033022968&fm=26&gp=0.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Female</td>\n",
       "      <td>65.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        性别    年龄     微笑      情绪\n",
       "值   Female  65.0  100.0     NaN\n",
       "阈值     NaN   NaN   50.0     NaN\n",
       "生气     NaN   NaN    NaN   0.269\n",
       "厌恶     NaN   NaN    NaN   0.008\n",
       "恐惧     NaN   NaN    NaN   0.011\n",
       "幸福     NaN   NaN    NaN  99.445\n",
       "中性     NaN   NaN    NaN   0.008\n",
       "悲伤     NaN   NaN    NaN   0.068\n",
       "惊喜     NaN   NaN    NaN   0.190"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# (['值','阈值','生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "# https://ss1.bdstatic.com/70cFuXSh_Q1YnxGkpoWK1HF6hhy/it/u=180314823,2033022968&fm=26&gp=0.jpg\n",
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"EDwY**************2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YUx**************svXO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://ss1.bdstatic.com/70cFuXSh_Q1YnxGkpoWK1HF6hhy/it/u=180314823,2033022968&fm=26&gp=0.jpg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 疲惫的司机\n",
    "![疲惫](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231460789&di=3cf2ac7054432d891553cc1ce6d88c93&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20180602%2F2a473e18db614de2bbd1c56fb3a85c1a.jpeg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1.766</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.068</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄      微笑      情绪\n",
       "值   Male  32.0   1.766     NaN\n",
       "阈值   NaN   NaN  50.000     NaN\n",
       "生气   NaN   NaN     NaN   0.388\n",
       "厌恶   NaN   NaN     NaN   0.016\n",
       "恐惧   NaN   NaN     NaN   0.023\n",
       "幸福   NaN   NaN     NaN   0.025\n",
       "中性   NaN   NaN     NaN   0.280\n",
       "悲伤   NaN   NaN     NaN  99.199\n",
       "惊喜   NaN   NaN     NaN   0.068"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231460789&di=3cf2ac7054432d891553cc1ce6d88c93&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20180602%2F2a473e18db614de2bbd1c56fb3a85c1a.jpeg\n",
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"ED**************H2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YUx**************XO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231460789&di=3cf2ac7054432d891553cc1ce6d88c93&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20180602%2F2a473e18db614de2bbd1c56fb3a85c1a.jpeg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 精神的司机\n",
    "![精神](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231563881&di=8422d6df2990a3b6cb3299bffc322fc8&imgtype=0&src=http%3A%2F%2Fzkres1.myzaker.com%2F201805%2F5afc5df277ac642dec28c9b2_640.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>36.0</td>\n",
       "      <td>99.967</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄      微笑      情绪\n",
       "值   Male  36.0  99.967     NaN\n",
       "阈值   NaN   NaN  50.000     NaN\n",
       "生气   NaN   NaN     NaN   0.001\n",
       "厌恶   NaN   NaN     NaN   0.101\n",
       "恐惧   NaN   NaN     NaN   0.001\n",
       "幸福   NaN   NaN     NaN  99.866\n",
       "中性   NaN   NaN     NaN   0.031\n",
       "悲伤   NaN   NaN     NaN   0.001\n",
       "惊喜   NaN   NaN     NaN   0.001"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231563881&di=8422d6df2990a3b6cb3299bffc322fc8&imgtype=0&src=http%3A%2F%2Fzkres1.myzaker.com%2F201805%2F5afc5df277ac642dec28c9b2_640.jpg\n",
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"EDw**************2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YUxY**************svXO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231563881&di=8422d6df2990a3b6cb3299bffc322fc8&imgtype=0&src=http%3A%2F%2Fzkres1.myzaker.com%2F201805%2F5afc5df277ac642dec28c9b2_640.jpg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 精神的司机\n",
    "![精神](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231563880&di=a352fec1adfaeb6273f2036a89dad85c&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20171103%2F97ced20c8c1944cf93e69fe24427d22c.jpeg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>48.0</td>\n",
       "      <td>97.229</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄      微笑      情绪\n",
       "值   Male  48.0  97.229     NaN\n",
       "阈值   NaN   NaN  50.000     NaN\n",
       "生气   NaN   NaN     NaN   0.004\n",
       "厌恶   NaN   NaN     NaN   0.010\n",
       "恐惧   NaN   NaN     NaN   0.025\n",
       "幸福   NaN   NaN     NaN  75.813\n",
       "中性   NaN   NaN     NaN  24.127\n",
       "悲伤   NaN   NaN     NaN   0.015\n",
       "惊喜   NaN   NaN     NaN   0.004"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231563880&di=a352fec1adfaeb6273f2036a89dad85c&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20171103%2F97ced20c8c1944cf93e69fe24427d22c.jpeg\n",
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"ED**************G\" # \"填上你的KEY\"\n",
    "api_secret = \"YU**************XO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594231563880&di=a352fec1adfaeb6273f2036a89dad85c&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20171103%2F97ced20c8c1944cf93e69fe24427d22c.jpeg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 疲劳的司机\n",
    "![疲劳](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233206151&di=a1fc79f08143e3b3c5525111f3fcdee2&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20170920%2Fe1ff7db155f041b49997dd57adc60b86.jpeg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>21.0</td>\n",
       "      <td>46.765</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.042</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄      微笑      情绪\n",
       "值   Male  21.0  46.765     NaN\n",
       "阈值   NaN   NaN  50.000     NaN\n",
       "生气   NaN   NaN     NaN   0.136\n",
       "厌恶   NaN   NaN     NaN   0.282\n",
       "恐惧   NaN   NaN     NaN   0.042\n",
       "幸福   NaN   NaN     NaN   1.710\n",
       "中性   NaN   NaN     NaN  96.390\n",
       "悲伤   NaN   NaN     NaN   1.399\n",
       "惊喜   NaN   NaN     NaN   0.042"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233206151&di=a1fc79f08143e3b3c5525111f3fcdee2&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20170920%2Fe1ff7db155f041b49997dd57adc60b86.jpegBASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'\n",
    "api_key = \"ED**************H2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YU**************XO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233206151&di=a1fc79f08143e3b3c5525111f3fcdee2&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20170920%2Fe1ff7db155f041b49997dd57adc60b86.jpeg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 疲劳的司机\n",
    "![疲劳](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233353080&di=4107772a9c3fbca3a8e5a12860c5a102&imgtype=0&src=http%3A%2F%2Fimg4.cache.netease.com%2Fauto%2F2014%2F8%2F19%2F20140819181906e39da_550.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.165</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄    微笑      情绪\n",
       "值   Male  33.0   0.0     NaN\n",
       "阈值   NaN   NaN  50.0     NaN\n",
       "生气   NaN   NaN   NaN   0.302\n",
       "厌恶   NaN   NaN   NaN   0.258\n",
       "恐惧   NaN   NaN   NaN  64.290\n",
       "幸福   NaN   NaN   NaN   0.070\n",
       "中性   NaN   NaN   NaN  27.570\n",
       "悲伤   NaN   NaN   NaN   7.346\n",
       "惊喜   NaN   NaN   NaN   0.165"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233353080&di=4107772a9c3fbca3a8e5a12860c5a102&imgtype=0&src=http%3A%2F%2Fimg4.cache.netease.com%2Fauto%2F2014%2F8%2F19%2F20140819181906e39da_550.jpg\n",
    "api_key = \"ED**************2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YU**************XO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233353080&di=4107772a9c3fbca3a8e5a12860c5a102&imgtype=0&src=http%3A%2F%2Fimg4.cache.netease.com%2Fauto%2F2014%2F8%2F19%2F20140819181906e39da_550.jpg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 精神的司机\n",
    "![精神](https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233464850&di=8d93adaa558963cbd5fa5cf780a09be2&imgtype=0&src=http%3A%2F%2Fimages.china.cn%2Fnews%2Fattachement%2Fjpg%2Fsite3%2F20141104%2F5197236820155545542.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>37.0</td>\n",
       "      <td>99.999</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.151</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄      微笑      情绪\n",
       "值   Male  37.0  99.999     NaN\n",
       "阈值   NaN   NaN  50.000     NaN\n",
       "生气   NaN   NaN     NaN   0.008\n",
       "厌恶   NaN   NaN     NaN   0.008\n",
       "恐惧   NaN   NaN     NaN   0.008\n",
       "幸福   NaN   NaN     NaN  99.711\n",
       "中性   NaN   NaN     NaN   0.095\n",
       "悲伤   NaN   NaN     NaN   0.020\n",
       "惊喜   NaN   NaN     NaN   0.151"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233464850&di=8d93adaa558963cbd5fa5cf780a09be2&imgtype=0&src=http%3A%2F%2Fimages.china.cn%2Fnews%2Fattachement%2Fjpg%2Fsite3%2F20141104%2F5197236820155545542.jpg\n",
    "api_key = \"EDwY**************H2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YU**************O\" # \"填上你的SECRET\"\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1594233464850&di=8d93adaa558963cbd5fa5cf780a09be2&imgtype=0&src=http%3A%2F%2Fimages.china.cn%2Fnews%2Fattachement%2Fjpg%2Fsite3%2F20141104%2F5197236820155545542.jpg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 困倦\n",
    "![困倦](https://ss0.bdstatic.com/70cFvHSh_Q1YnxGkpoWK1HF6hhy/it/u=46168330,1807511450&fm=26&gp=0.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>性别</th>\n",
       "      <th>年龄</th>\n",
       "      <th>微笑</th>\n",
       "      <th>情绪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>Male</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.14</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阈值</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生气</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>厌恶</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>恐惧</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>幸福</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>悲伤</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>惊喜</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.057</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      性别    年龄     微笑      情绪\n",
       "值   Male  49.0   0.14     NaN\n",
       "阈值   NaN   NaN  50.00     NaN\n",
       "生气   NaN   NaN    NaN   2.290\n",
       "厌恶   NaN   NaN    NaN   0.047\n",
       "恐惧   NaN   NaN    NaN  33.324\n",
       "幸福   NaN   NaN    NaN   0.051\n",
       "中性   NaN   NaN    NaN  61.756\n",
       "悲伤   NaN   NaN    NaN   2.475\n",
       "惊喜   NaN   NaN    NaN   0.057"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://ss0.bdstatic.com/70cFvHSh_Q1YnxGkpoWK1HF6hhy/it/u=46168330,1807511450&fm=26&gp=0.jpg\n",
    "api_key = \"ED**************2G\" # \"填上你的KEY\"\n",
    "api_secret = \"YUx**************vXO\" # \"填上你的SECRET\"\n",
    "img_url = \"https://ss0.bdstatic.com/70cFvHSh_Q1YnxGkpoWK1HF6hhy/it/u=46168330,1807511450&fm=26&gp=0.jpg\"\n",
    "\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)\n",
    "results = r.json() # \n",
    "df = pd.DataFrame(results['faces'][0]['attributes'])\\\n",
    ".rename(columns = {\"gender\":\"性别\", \"age\":\"年龄\", \"smile\":\"微笑\", \"emotion\":\"情绪\"})\n",
    "df.index = Series(['值', '阈值', '生气','厌恶','恐惧','幸福','中性','悲伤','惊喜'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 找到好的休息场所"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'address': 'CN|广东|广州|None|UNICOM|0|0',\n",
       " 'content': {'address': '广东省广州市',\n",
       "  'address_detail': {'city': '广州市',\n",
       "   'city_code': 257,\n",
       "   'district': '',\n",
       "   'province': '广东省',\n",
       "   'street': '',\n",
       "   'street_number': ''},\n",
       "  'point': {'x': '113.30764968', 'y': '23.12004910'}},\n",
       " 'status': 0}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def IP(ip=None,sig=None)->dict:\n",
    "    url = 'http://api.map.baidu.com/location/ip'\n",
    "    params={\n",
    "        'ak':'7CaBK6jpvpA4WkxMujUkFfd2mPiR4d9e',\n",
    "        'ip':'61.242.54.52',\n",
    "        'coor':'bd09ll',\n",
    "        'sip':sig,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "IP()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': 0,\n",
       " 'result': {'location': {'lng': 23.119797546652453, 'lat': 85.09099187480457},\n",
       "  'formatted_address': '',\n",
       "  'business': '',\n",
       "  'addressComponent': {'country': '',\n",
       "   'country_code': -1,\n",
       "   'country_code_iso': '',\n",
       "   'country_code_iso2': '',\n",
       "   'province': '',\n",
       "   'city': '',\n",
       "   'city_level': 2,\n",
       "   'district': '',\n",
       "   'town': '',\n",
       "   'town_code': '',\n",
       "   'adcode': '0',\n",
       "   'street': '',\n",
       "   'street_number': '',\n",
       "   'direction': '',\n",
       "   'distance': ''},\n",
       "  'pois': [],\n",
       "  'roads': [],\n",
       "  'poiRegions': [],\n",
       "  'sematic_description': '',\n",
       "  'cityCode': 0}}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 逆地理编码\n",
    "# location ak http://api.map.baidu.com/reverse_geocoding/v3/?ak=您的ak&output=json&coordtype=wgs84ll&location=31.225696563611,121.49884033194\n",
    "\n",
    "def inverse(location=None)->dict:\n",
    "    url = 'http://api.map.baidu.com/reverse_geocoding/v3/'\n",
    "    params={\n",
    "        'ak':'7CaBK6jpvpA4WkxMujUkFfd2mPiR4d9e',\n",
    "        'location':'113.30764968,23.12004910',\n",
    "        'coor':'bd09ll',\n",
    "#         'sip':sig,\n",
    "        'output':'json',\n",
    "        'poi_types':'美食|酒店'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "inverse()\n",
    "# me"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我现在在学校，所以我另外使用一个经纬度来模拟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': 0,\n",
       " 'result': {'location': {'lng': 116.62947017362819, 'lat': 23.662623192615886},\n",
       "  'precise': 0,\n",
       "  'confidence': 20,\n",
       "  'comprehension': 57,\n",
       "  'level': '城市'}}"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 地理编码\n",
    "def geographic(address,city)->dict:\n",
    "    url = 'http://api.map.baidu.com/geocoding/v3/'\n",
    "    params={\n",
    "        'ak':'7CaBK6jpvpA4WkxMujUkFfd2mPiR4d9e',\n",
    "        'address':'113.30764968,23.12004910',\n",
    "        'cityret_coordtype':'bd09ll',\n",
    "        'city':city,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "geographic('潮州市潮安区安南路与亨利路交叉路口东南侧','潮州市')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': 0,\n",
       " 'result': {'location': {'lng': 23.662365735561913, 'lat': 85.09099187480457},\n",
       "  'formatted_address': '',\n",
       "  'business': '',\n",
       "  'addressComponent': {'country': '',\n",
       "   'country_code': -1,\n",
       "   'country_code_iso': '',\n",
       "   'country_code_iso2': '',\n",
       "   'province': '',\n",
       "   'city': '',\n",
       "   'city_level': 2,\n",
       "   'district': '',\n",
       "   'town': '',\n",
       "   'town_code': '',\n",
       "   'adcode': '0',\n",
       "   'street': '',\n",
       "   'street_number': '',\n",
       "   'direction': '',\n",
       "   'distance': ''},\n",
       "  'pois': [],\n",
       "  'roads': [],\n",
       "  'poiRegions': [],\n",
       "  'sematic_description': '',\n",
       "  'cityCode': 0}}"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def inverse(location=None)->dict:\n",
    "    url = 'http://api.map.baidu.com/reverse_geocoding/v3/'\n",
    "    params={\n",
    "        'ak':'7CaBK6jpvpA4WkxMujUkFfd2mPiR4d9e',\n",
    "        'location':'116.62947017362819,23.662623192615886',\n",
    "        'coor':'bd09ll',\n",
    "        'radius':1000,\n",
    "        'language_auto':1,\n",
    "        'output':'json',\n",
    "        'poi_types':'美食|酒店'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "inverse()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "key =\"9**************40\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': '1',\n",
       " 'info': 'OK',\n",
       " 'infocode': '10000',\n",
       " 'province': '广东省',\n",
       " 'city': '广州市',\n",
       " 'adcode': '440100',\n",
       " 'rectangle': '113.1017375,22.93212254;113.6770499,23.3809537'}"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def IP(ip=None,sig=None)->dict:\n",
    "    url = 'https://restapi.amap.com/v3/ip?parameters'\n",
    "    params={\n",
    "        'key':key,\n",
    "        'ip':ip,\n",
    "        'sip':sig,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "IP()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我现在在学校，所以我另外使用一个经纬度来模拟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': '1',\n",
       " 'info': 'OK',\n",
       " 'infocode': '10000',\n",
       " 'count': '1',\n",
       " 'geocodes': [{'formatted_address': '广东省潮州市潮安区安南路/亨利路',\n",
       "   'country': '中国',\n",
       "   'province': '广东省',\n",
       "   'citycode': '0768',\n",
       "   'city': '潮州市',\n",
       "   'district': '潮安区',\n",
       "   'township': [],\n",
       "   'neighborhood': {'name': [], 'type': []},\n",
       "   'building': {'name': [], 'type': []},\n",
       "   'adcode': '445103',\n",
       "   'street': [],\n",
       "   'number': [],\n",
       "   'location': '116.678113,23.453833',\n",
       "   'level': '道路交叉路口'}]}"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def geocode(address,city=None,batch=None,sig=None)->dict:\n",
    "    url = 'https://restapi.amap.com/v3/geocode/geo?parameters'\n",
    "    params={\n",
    "        'key': key,\n",
    "        'address':address,\n",
    "        'city':city,\n",
    "        'batch':batch,\n",
    "        'sig':sig,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "#     data_df = json_normalize(response.json()['geocodes'])\n",
    "    return data\n",
    "geocode('潮州市潮安区安南路与亨利路交叉路口东南侧',city='潮州市')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': '1',\n",
       " 'regeocode': {'roads': [{'id': '0754F50F00702250',\n",
       "    'location': '116.678,23.4538',\n",
       "    'direction': 'Center',\n",
       "    'name': '亨利路',\n",
       "    'distance': '0'},\n",
       "   {'id': '0754F50F0070222901',\n",
       "    'location': '116.678,23.4538',\n",
       "    'direction': '东南',\n",
       "    'name': '安南路',\n",
       "    'distance': '2.52721'},\n",
       "   {'id': '0754F50F0070225231',\n",
       "    'location': '116.677,23.4543',\n",
       "    'direction': '东南',\n",
       "    'name': '桑浦街',\n",
       "    'distance': '93.5452'}],\n",
       "  'roadinters': [{'second_name': '亨利路',\n",
       "    'first_id': '0754F50F0070222901',\n",
       "    'second_id': '0754F50F00702250',\n",
       "    'location': '116.678095,23.45384889',\n",
       "    'distance': '2.54804',\n",
       "    'first_name': '安南路',\n",
       "    'direction': '东南'}],\n",
       "  'formatted_address': '广东省潮州市潮安区庵埠镇亨利路声乐大酒店',\n",
       "  'addressComponent': {'city': '潮州市',\n",
       "   'province': '广东省',\n",
       "   'adcode': '445103',\n",
       "   'district': '潮安区',\n",
       "   'towncode': '445103110000',\n",
       "   'streetNumber': {'number': '7号',\n",
       "    'location': '116.678103,23.4535694',\n",
       "    'direction': '南',\n",
       "    'distance': '29.3313',\n",
       "    'street': '安南路'},\n",
       "   'country': '中国',\n",
       "   'township': '庵埠镇',\n",
       "   'businessAreas': [[]],\n",
       "   'building': {'name': [], 'type': []},\n",
       "   'neighborhood': {'name': [], 'type': []},\n",
       "   'citycode': '0768'},\n",
       "  'aois': [{'area': '5111.912245',\n",
       "    'type': '100103',\n",
       "    'id': 'B030000E2W',\n",
       "    'location': '116.678116,23.453059',\n",
       "    'adcode': '445103',\n",
       "    'name': '声乐大酒店',\n",
       "    'distance': '29.6637'}],\n",
       "  'pois': [{'id': 'B030000E2W',\n",
       "    'direction': '南',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利北路',\n",
       "    'poiweight': '0.511695',\n",
       "    'name': '声乐大酒店',\n",
       "    'location': '116.678116,23.453059',\n",
       "    'distance': '86.0879',\n",
       "    'tel': '0768-6669338;0768-5829338',\n",
       "    'type': '住宿服务;宾馆酒店;四星级宾馆'},\n",
       "   {'id': 'B0FFFY9DYW',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利北路8栋1-2楼',\n",
       "    'poiweight': '0.147962',\n",
       "    'name': '商业幼儿园',\n",
       "    'location': '116.678654,23.453098',\n",
       "    'distance': '98.6107',\n",
       "    'tel': [],\n",
       "    'type': '科教文化服务;科教文化场所;科教文化场所'},\n",
       "   {'id': 'B030000UN6',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利北路',\n",
       "    'poiweight': '0.177073',\n",
       "    'name': '中国信合(庵埠信用社)',\n",
       "    'location': '116.679709,23.452192',\n",
       "    'distance': '244.552',\n",
       "    'tel': [],\n",
       "    'type': '金融保险服务;银行;农村商业银行'},\n",
       "   {'id': 'B03000MT2B',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇文里村',\n",
       "    'poiweight': '0.147726',\n",
       "    'name': '潮安区启明星培训学校',\n",
       "    'location': '116.679128,23.452181',\n",
       "    'distance': '210.869',\n",
       "    'tel': '0768-5812933',\n",
       "    'type': '科教文化服务;培训机构;培训机构'},\n",
       "   {'id': 'B0FFH6C3N2',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '文里村安南路北门外片一幢甲向6号',\n",
       "    'poiweight': '0.153911',\n",
       "    'name': '天意电脑培训',\n",
       "    'location': '116.678933,23.455437',\n",
       "    'distance': '196.995',\n",
       "    'tel': '0768-6625032;13829085081',\n",
       "    'type': '科教文化服务;培训机构;培训机构'},\n",
       "   {'id': 'B030000ULG',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇亨利路5号',\n",
       "    'poiweight': '0.371161',\n",
       "    'name': '文里学校',\n",
       "    'location': '116.680109,23.452638',\n",
       "    'distance': '243.129',\n",
       "    'tel': '0768-6666993',\n",
       "    'type': '科教文化服务;学校;学校'},\n",
       "   {'id': 'B030000PD3',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇文里亨利路',\n",
       "    'poiweight': '0.140638',\n",
       "    'name': '文里蓓蕾园',\n",
       "    'location': '116.679052,23.452831',\n",
       "    'distance': '146.926',\n",
       "    'tel': [],\n",
       "    'type': '商务住宅;住宅区;住宅小区'},\n",
       "   {'id': 'B030000UN5',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇亨利北路中段',\n",
       "    'poiweight': '0.279456',\n",
       "    'name': '中国建设银行(庵埠支行)',\n",
       "    'location': '116.679990,23.451950',\n",
       "    'distance': '283.741',\n",
       "    'tel': '0768-6665200',\n",
       "    'type': '金融保险服务;银行;中国建设银行'},\n",
       "   {'id': 'B030000URJ',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇亨利北路声乐大酒店后面3号',\n",
       "    'poiweight': '0.185907',\n",
       "    'name': '新金田彩印实业有限公司',\n",
       "    'location': '116.679085,23.454393',\n",
       "    'distance': '117.084',\n",
       "    'tel': '0768-5880888',\n",
       "    'type': '公司企业;公司;公司'},\n",
       "   {'id': 'B030000URH',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '喜乐大厦斜对面',\n",
       "    'poiweight': '0.341181',\n",
       "    'name': '好口味大排档(安南路店)',\n",
       "    'location': '116.678737,23.454354',\n",
       "    'distance': '86.0521',\n",
       "    'tel': '0768-6623838',\n",
       "    'type': '餐饮服务;中餐厅;中餐厅'},\n",
       "   {'id': 'B0FFH6C3RT',\n",
       "    'direction': '北',\n",
       "    'businessarea': [],\n",
       "    'address': '安南路与韩江街交叉口西南150米',\n",
       "    'poiweight': '0.144329',\n",
       "    'name': '正合堂',\n",
       "    'location': '116.678520,23.454839',\n",
       "    'distance': '119.304',\n",
       "    'tel': [],\n",
       "    'type': '医疗保健服务;医疗保健服务场所;医疗保健服务场所'},\n",
       "   {'id': 'B030000PD5',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇安南路',\n",
       "    'poiweight': '0.261896',\n",
       "    'name': '现代女子门诊部',\n",
       "    'location': '116.678979,23.454753',\n",
       "    'distance': '135.157',\n",
       "    'tel': [],\n",
       "    'type': '医疗保健服务;诊所;诊所'},\n",
       "   {'id': 'B030000PD4',\n",
       "    'direction': '西北',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠文里崎桥工业区玉石街1号',\n",
       "    'poiweight': '0.25487',\n",
       "    'name': '广东中包机械有限公司',\n",
       "    'location': '116.676226,23.454889',\n",
       "    'distance': '225.472',\n",
       "    'tel': [],\n",
       "    'type': '公司企业;公司;公司'},\n",
       "   {'id': 'B030000YXN',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利路与文里文西路交叉口东南100米',\n",
       "    'poiweight': '0.232829',\n",
       "    'name': '潮安区房地产交易所',\n",
       "    'location': '116.679349,23.452501',\n",
       "    'distance': '194.503',\n",
       "    'tel': [],\n",
       "    'type': '政府机构及社会团体;政府机关;政府机关相关'},\n",
       "   {'id': 'B0FFH6C3PA',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '安南路与韩江街交叉口西南150米',\n",
       "    'poiweight': '0.167016',\n",
       "    'name': '正合食品有限公司',\n",
       "    'location': '116.678597,23.454950',\n",
       "    'distance': '133.654',\n",
       "    'tel': '0768-6619019',\n",
       "    'type': '公司企业;公司;公司'},\n",
       "   {'id': 'B0FFLJV8DD',\n",
       "    'direction': '北',\n",
       "    'businessarea': [],\n",
       "    'address': [],\n",
       "    'poiweight': '0.197706',\n",
       "    'name': '锦山楼',\n",
       "    'location': '116.678560,23.455357',\n",
       "    'distance': '175.483',\n",
       "    'tel': [],\n",
       "    'type': '商务住宅;楼宇;楼宇相关'},\n",
       "   {'id': 'B03000MU8U',\n",
       "    'direction': '西南',\n",
       "    'businessarea': [],\n",
       "    'address': '侨文路与安南路交叉口南100米',\n",
       "    'poiweight': '0.254024',\n",
       "    'name': '鸿达住宿',\n",
       "    'location': '116.676815,23.451795',\n",
       "    'distance': '262.482',\n",
       "    'tel': '0768-6670066;13531524235',\n",
       "    'type': '住宿服务;旅馆招待所;旅馆招待所'},\n",
       "   {'id': 'B0FFHPSRVC',\n",
       "    'direction': '西南',\n",
       "    'businessarea': [],\n",
       "    'address': '文里村侨文路中段(潮味排挡往西三十米处)',\n",
       "    'poiweight': '0.15748',\n",
       "    'name': '换模式公寓',\n",
       "    'location': '116.676656,23.452839',\n",
       "    'distance': '185.234',\n",
       "    'tel': '18933498690;13923351780',\n",
       "    'type': '商务住宅;商务住宅相关;商务住宅相关'},\n",
       "   {'id': 'B0FFKZNE2O',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇安南路中段亨安旅馆对面(交通银行隔壁)',\n",
       "    'poiweight': '0.175302',\n",
       "    'name': '英加教育',\n",
       "    'location': '116.679274,23.455146',\n",
       "    'distance': '187.996',\n",
       "    'tel': [],\n",
       "    'type': '科教文化服务;科教文化场所;科教文化场所'},\n",
       "   {'id': 'B0FFHTTRSO',\n",
       "    'direction': '北',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇安南路亨安宾馆向南60米',\n",
       "    'poiweight': '0.235249',\n",
       "    'name': '逍遥公寓',\n",
       "    'location': '116.678109,23.455545',\n",
       "    'distance': '190.369',\n",
       "    'tel': '13778333382',\n",
       "    'type': '商务住宅;商务住宅相关;商务住宅相关'},\n",
       "   {'id': 'B0FFH63UOE',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇文里村亨利北路文里小学运动场隔壁',\n",
       "    'poiweight': '0.157045',\n",
       "    'name': '潮香饼屋',\n",
       "    'location': '116.679004,23.452798',\n",
       "    'distance': '146.645',\n",
       "    'tel': '13631015977;13435597205',\n",
       "    'type': '餐饮服务;餐饮相关场所;餐饮相关'},\n",
       "   {'id': 'B0FFH6C3NI',\n",
       "    'direction': '西北',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利路与茂林街交叉口东南50米',\n",
       "    'poiweight': '0.165616',\n",
       "    'name': '金基胶带',\n",
       "    'location': '116.676800,23.454762',\n",
       "    'distance': '169.149',\n",
       "    'tel': [],\n",
       "    'type': '购物服务;购物相关场所;购物相关场所'},\n",
       "   {'id': 'B0FFH6C3MU',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '庵埠镇安南路中段达标大酒店附近',\n",
       "    'poiweight': '0.149866',\n",
       "    'name': '韩宫社',\n",
       "    'location': '116.679473,23.456241',\n",
       "    'distance': '301.582',\n",
       "    'tel': '15913009260',\n",
       "    'type': '餐饮服务;餐饮相关场所;餐饮相关'},\n",
       "   {'id': 'B030000WIV',\n",
       "    'direction': '东北',\n",
       "    'businessarea': [],\n",
       "    'address': '亨安旅馆附近',\n",
       "    'poiweight': '0.414814',\n",
       "    'name': '大卡司(庵埠店)',\n",
       "    'location': '116.679017,23.455568',\n",
       "    'distance': '213.834',\n",
       "    'tel': '13690043210',\n",
       "    'type': '餐饮服务;冷饮店;冷饮店'},\n",
       "   {'id': 'B0FFHPB6ZW',\n",
       "    'direction': '南',\n",
       "    'businessarea': [],\n",
       "    'address': '侨文路北侧',\n",
       "    'poiweight': '0.237623',\n",
       "    'name': '汇福名苑',\n",
       "    'location': '116.678083,23.451934',\n",
       "    'distance': '211.21',\n",
       "    'tel': [],\n",
       "    'type': '商务住宅;住宅区;住宅小区'},\n",
       "   {'id': 'B0FFLJWV5M',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': [],\n",
       "    'poiweight': '0.147627',\n",
       "    'name': '印象启明星美术教育',\n",
       "    'location': '116.679064,23.452119',\n",
       "    'distance': '213.876',\n",
       "    'tel': [],\n",
       "    'type': '科教文化服务;培训机构;培训机构'},\n",
       "   {'id': 'B0FFHTZACQ',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利路与文里文西路交叉口南150米',\n",
       "    'poiweight': '0.145419',\n",
       "    'name': '庵埠镇所人口和计划生育服务站',\n",
       "    'location': '116.678990,23.452044',\n",
       "    'distance': '218.143',\n",
       "    'tel': [],\n",
       "    'type': '政府机构及社会团体;政府机关;乡镇级政府及事业单位'},\n",
       "   {'id': 'B0FFLJXG6K',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': [],\n",
       "    'poiweight': '0.130417',\n",
       "    'name': '庵埠镇人口和计划生育办公室',\n",
       "    'location': '116.678932,23.451989',\n",
       "    'distance': '221.434',\n",
       "    'tel': [],\n",
       "    'type': '政府机构及社会团体;政府机关;乡镇级政府及事业单位'},\n",
       "   {'id': 'B0FFLM2MK4',\n",
       "    'direction': '东南',\n",
       "    'businessarea': [],\n",
       "    'address': [],\n",
       "    'poiweight': '0.130336',\n",
       "    'name': '庵埠镇创建教育强镇办公室',\n",
       "    'location': '116.678914,23.451970',\n",
       "    'distance': '222.698',\n",
       "    'tel': [],\n",
       "    'type': '政府机构及社会团体;政府机关;乡镇级政府及事业单位'},\n",
       "   {'id': 'B0FFI9OYSJ',\n",
       "    'direction': '西北',\n",
       "    'businessarea': [],\n",
       "    'address': '亨利路与桑浦街交叉口西50米',\n",
       "    'poiweight': '0.207743',\n",
       "    'name': '江西瑞金小炒',\n",
       "    'location': '116.677238,23.454406',\n",
       "    'distance': '109.673',\n",
       "    'tel': '13715795016;13715817029',\n",
       "    'type': '餐饮服务;中餐厅;中餐厅'}]},\n",
       " 'info': 'OK',\n",
       " 'infocode': '10000'}"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def regeocode(location,poitype=None,radius=None,extensions=\"all\",batch=False,roadlevel=None,sig=None,homeorcorp=None)->dict:\n",
    "    \"\"\"获取逆地理编码\"\"\"\n",
    "    url = 'https://restapi.amap.com/v3/geocode/regeo?parameters'\n",
    "    params={\n",
    "        'key': key,\n",
    "        'location':location,\n",
    "        'poitype':poitype,\n",
    "        'radius':radius,\n",
    "        'extensions':extensions,\n",
    "        'batch':batch,\n",
    "        'roadlevel':roadlevel,\n",
    "        'homeorcorp':homeorcorp,\n",
    "        'sig':sig,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "regeocode( '116.678113,23.453833')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.io.json import json_normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>tel</th>\n",
       "      <th>direction</th>\n",
       "      <th>distance</th>\n",
       "      <th>location</th>\n",
       "      <th>address</th>\n",
       "      <th>poiweight</th>\n",
       "      <th>businessarea</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B030000E2W</td>\n",
       "      <td>声乐大酒店</td>\n",
       "      <td>住宿服务;宾馆酒店;四星级宾馆</td>\n",
       "      <td>0768-6669338;0768-5829338</td>\n",
       "      <td>南</td>\n",
       "      <td>86.0879</td>\n",
       "      <td>116.678116,23.453059</td>\n",
       "      <td>亨利北路</td>\n",
       "      <td>0.511695</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>B03000MU8U</td>\n",
       "      <td>鸿达住宿</td>\n",
       "      <td>住宿服务;旅馆招待所;旅馆招待所</td>\n",
       "      <td>0768-6670066;13531524235</td>\n",
       "      <td>西南</td>\n",
       "      <td>262.482</td>\n",
       "      <td>116.676815,23.451795</td>\n",
       "      <td>侨文路与安南路交叉口南100米</td>\n",
       "      <td>0.254024</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id   name              type                        tel direction  \\\n",
       "0   B030000E2W  声乐大酒店   住宿服务;宾馆酒店;四星级宾馆  0768-6669338;0768-5829338         南   \n",
       "16  B03000MU8U   鸿达住宿  住宿服务;旅馆招待所;旅馆招待所   0768-6670066;13531524235        西南   \n",
       "\n",
       "   distance              location          address poiweight businessarea  \n",
       "0   86.0879  116.678116,23.453059             亨利北路  0.511695           []  \n",
       "16  262.482  116.676815,23.451795  侨文路与安南路交叉口南100米  0.254024           []  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poi_all = regeocode( '116.678113,23.453833',poitype='住宿服务')\n",
    "poi_all['regeocode']['pois']\n",
    "poi_df = json_normalize(poi_all['regeocode']['pois'])\n",
    "df_住宿服务 = poi_df[poi_df[\"type\"].str.contains(\"住宿服务\")]\n",
    "df_住宿服务"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>direction</th>\n",
       "      <th>businessarea</th>\n",
       "      <th>address</th>\n",
       "      <th>poiweight</th>\n",
       "      <th>name</th>\n",
       "      <th>location</th>\n",
       "      <th>distance</th>\n",
       "      <th>tel</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B030000E2W</td>\n",
       "      <td>南</td>\n",
       "      <td>[]</td>\n",
       "      <td>亨利北路</td>\n",
       "      <td>0.511695</td>\n",
       "      <td>声乐大酒店</td>\n",
       "      <td>116.678116,23.453059</td>\n",
       "      <td>86.0879</td>\n",
       "      <td>0768-6669338;0768-5829338</td>\n",
       "      <td>住宿服务;宾馆酒店;四星级宾馆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>B03000MU8U</td>\n",
       "      <td>西南</td>\n",
       "      <td>[]</td>\n",
       "      <td>侨文路与安南路交叉口南100米</td>\n",
       "      <td>0.254024</td>\n",
       "      <td>鸿达住宿</td>\n",
       "      <td>116.676815,23.451795</td>\n",
       "      <td>262.482</td>\n",
       "      <td>0768-6670066;13531524235</td>\n",
       "      <td>住宿服务;旅馆招待所;旅馆招待所</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id direction businessarea          address poiweight   name  \\\n",
       "0   B030000E2W         南           []             亨利北路  0.511695  声乐大酒店   \n",
       "16  B03000MU8U        西南           []  侨文路与安南路交叉口南100米  0.254024   鸿达住宿   \n",
       "\n",
       "                location distance                        tel              type  \n",
       "0   116.678116,23.453059  86.0879  0768-6669338;0768-5829338   住宿服务;宾馆酒店;四星级宾馆  \n",
       "16  116.676815,23.451795  262.482   0768-6670066;13531524235  住宿服务;旅馆招待所;旅馆招待所  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poi_all = regeocode( '116.678113,23.453833')\n",
    "poi_all['regeocode']['pois']\n",
    "poi_df = json_normalize(poi_all['regeocode']['pois'])\n",
    "# poi_df\n",
    "df_住宿服务 = poi_df[poi_df[\"type\"].str.contains(\"住宿服务\")]\n",
    "df_住宿服务"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>tel</th>\n",
       "      <th>direction</th>\n",
       "      <th>distance</th>\n",
       "      <th>location</th>\n",
       "      <th>address</th>\n",
       "      <th>poiweight</th>\n",
       "      <th>businessarea</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>B030000URH</td>\n",
       "      <td>好口味大排档(安南路店)</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>0768-6623838</td>\n",
       "      <td>东北</td>\n",
       "      <td>86.0521</td>\n",
       "      <td>116.678737,23.454354</td>\n",
       "      <td>喜乐大厦斜对面</td>\n",
       "      <td>0.341181</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>B0FFH63UOE</td>\n",
       "      <td>潮香饼屋</td>\n",
       "      <td>餐饮服务;餐饮相关场所;餐饮相关</td>\n",
       "      <td>13631015977;13435597205</td>\n",
       "      <td>东南</td>\n",
       "      <td>146.645</td>\n",
       "      <td>116.679004,23.452798</td>\n",
       "      <td>庵埠镇文里村亨利北路文里小学运动场隔壁</td>\n",
       "      <td>0.157045</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>B0FFH6C3MU</td>\n",
       "      <td>韩宫社</td>\n",
       "      <td>餐饮服务;餐饮相关场所;餐饮相关</td>\n",
       "      <td>15913009260</td>\n",
       "      <td>东北</td>\n",
       "      <td>301.582</td>\n",
       "      <td>116.679473,23.456241</td>\n",
       "      <td>庵埠镇安南路中段达标大酒店附近</td>\n",
       "      <td>0.149866</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>B030000WIV</td>\n",
       "      <td>大卡司(庵埠店)</td>\n",
       "      <td>餐饮服务;冷饮店;冷饮店</td>\n",
       "      <td>13690043210</td>\n",
       "      <td>东北</td>\n",
       "      <td>213.834</td>\n",
       "      <td>116.679017,23.455568</td>\n",
       "      <td>亨安旅馆附近</td>\n",
       "      <td>0.414814</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>B0FFI9OYSJ</td>\n",
       "      <td>江西瑞金小炒</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>13715795016;13715817029</td>\n",
       "      <td>西北</td>\n",
       "      <td>109.673</td>\n",
       "      <td>116.677238,23.454406</td>\n",
       "      <td>亨利路与桑浦街交叉口西50米</td>\n",
       "      <td>0.207743</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B030000E2W</td>\n",
       "      <td>声乐大酒店</td>\n",
       "      <td>住宿服务;宾馆酒店;四星级宾馆</td>\n",
       "      <td>0768-6669338;0768-5829338</td>\n",
       "      <td>南</td>\n",
       "      <td>86.0879</td>\n",
       "      <td>116.678116,23.453059</td>\n",
       "      <td>亨利北路</td>\n",
       "      <td>0.511695</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>B03000MU8U</td>\n",
       "      <td>鸿达住宿</td>\n",
       "      <td>住宿服务;旅馆招待所;旅馆招待所</td>\n",
       "      <td>0768-6670066;13531524235</td>\n",
       "      <td>西南</td>\n",
       "      <td>262.482</td>\n",
       "      <td>116.676815,23.451795</td>\n",
       "      <td>侨文路与安南路交叉口南100米</td>\n",
       "      <td>0.254024</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id          name              type                        tel  \\\n",
       "9   B030000URH  好口味大排档(安南路店)      餐饮服务;中餐厅;中餐厅               0768-6623838   \n",
       "20  B0FFH63UOE          潮香饼屋  餐饮服务;餐饮相关场所;餐饮相关    13631015977;13435597205   \n",
       "22  B0FFH6C3MU           韩宫社  餐饮服务;餐饮相关场所;餐饮相关                15913009260   \n",
       "23  B030000WIV      大卡司(庵埠店)      餐饮服务;冷饮店;冷饮店                13690043210   \n",
       "29  B0FFI9OYSJ        江西瑞金小炒      餐饮服务;中餐厅;中餐厅    13715795016;13715817029   \n",
       "0   B030000E2W         声乐大酒店   住宿服务;宾馆酒店;四星级宾馆  0768-6669338;0768-5829338   \n",
       "16  B03000MU8U          鸿达住宿  住宿服务;旅馆招待所;旅馆招待所   0768-6670066;13531524235   \n",
       "\n",
       "   direction distance              location              address poiweight  \\\n",
       "9         东北  86.0521  116.678737,23.454354              喜乐大厦斜对面  0.341181   \n",
       "20        东南  146.645  116.679004,23.452798  庵埠镇文里村亨利北路文里小学运动场隔壁  0.157045   \n",
       "22        东北  301.582  116.679473,23.456241      庵埠镇安南路中段达标大酒店附近  0.149866   \n",
       "23        东北  213.834  116.679017,23.455568               亨安旅馆附近  0.414814   \n",
       "29        西北  109.673  116.677238,23.454406       亨利路与桑浦街交叉口西50米  0.207743   \n",
       "0          南  86.0879  116.678116,23.453059                 亨利北路  0.511695   \n",
       "16        西南  262.482  116.676815,23.451795      侨文路与安南路交叉口南100米  0.254024   \n",
       "\n",
       "   businessarea  \n",
       "9            []  \n",
       "20           []  \n",
       "22           []  \n",
       "23           []  \n",
       "29           []  \n",
       "0            []  \n",
       "16           []  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "poi_all = regeocode( '116.678113,23.453833',poitype='住宿服务')\n",
    "poi_all['regeocode']['pois']\n",
    "poi_df = json_normalize(poi_all['regeocode']['pois'])\n",
    "df_住宿服务 = poi_df[poi_df[\"type\"].str.contains(\"住宿服务\")]\n",
    "df_餐饮服务 = poi_df[poi_df[\"type\"].str.contains(\"餐饮服务\")]\n",
    "休息场所_df = pd.concat([df_餐饮服务, df_住宿服务], axis=0)\n",
    "display(休息场所_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>tel</th>\n",
       "      <th>direction</th>\n",
       "      <th>distance</th>\n",
       "      <th>location</th>\n",
       "      <th>address</th>\n",
       "      <th>poiweight</th>\n",
       "      <th>businessarea</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>B030000URH</td>\n",
       "      <td>好口味大排档(安南路店)</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>0768-6623838</td>\n",
       "      <td>东北</td>\n",
       "      <td>86.0521</td>\n",
       "      <td>116.678737,23.454354</td>\n",
       "      <td>喜乐大厦斜对面</td>\n",
       "      <td>0.341181</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>B0FFH63UOE</td>\n",
       "      <td>潮香饼屋</td>\n",
       "      <td>餐饮服务;餐饮相关场所;餐饮相关</td>\n",
       "      <td>13631015977;13435597205</td>\n",
       "      <td>东南</td>\n",
       "      <td>146.645</td>\n",
       "      <td>116.679004,23.452798</td>\n",
       "      <td>庵埠镇文里村亨利北路文里小学运动场隔壁</td>\n",
       "      <td>0.157045</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>B0FFH6C3MU</td>\n",
       "      <td>韩宫社</td>\n",
       "      <td>餐饮服务;餐饮相关场所;餐饮相关</td>\n",
       "      <td>15913009260</td>\n",
       "      <td>东北</td>\n",
       "      <td>301.582</td>\n",
       "      <td>116.679473,23.456241</td>\n",
       "      <td>庵埠镇安南路中段达标大酒店附近</td>\n",
       "      <td>0.149866</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>B030000WIV</td>\n",
       "      <td>大卡司(庵埠店)</td>\n",
       "      <td>餐饮服务;冷饮店;冷饮店</td>\n",
       "      <td>13690043210</td>\n",
       "      <td>东北</td>\n",
       "      <td>213.834</td>\n",
       "      <td>116.679017,23.455568</td>\n",
       "      <td>亨安旅馆附近</td>\n",
       "      <td>0.414814</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>B0FFI9OYSJ</td>\n",
       "      <td>江西瑞金小炒</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>13715795016;13715817029</td>\n",
       "      <td>西北</td>\n",
       "      <td>109.673</td>\n",
       "      <td>116.677238,23.454406</td>\n",
       "      <td>亨利路与桑浦街交叉口西50米</td>\n",
       "      <td>0.207743</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B030000E2W</td>\n",
       "      <td>声乐大酒店</td>\n",
       "      <td>住宿服务;宾馆酒店;四星级宾馆</td>\n",
       "      <td>0768-6669338;0768-5829338</td>\n",
       "      <td>南</td>\n",
       "      <td>86.0879</td>\n",
       "      <td>116.678116,23.453059</td>\n",
       "      <td>亨利北路</td>\n",
       "      <td>0.511695</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>B03000MU8U</td>\n",
       "      <td>鸿达住宿</td>\n",
       "      <td>住宿服务;旅馆招待所;旅馆招待所</td>\n",
       "      <td>0768-6670066;13531524235</td>\n",
       "      <td>西南</td>\n",
       "      <td>262.482</td>\n",
       "      <td>116.676815,23.451795</td>\n",
       "      <td>侨文路与安南路交叉口南100米</td>\n",
       "      <td>0.254024</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id          name              type                        tel  \\\n",
       "9   B030000URH  好口味大排档(安南路店)      餐饮服务;中餐厅;中餐厅               0768-6623838   \n",
       "20  B0FFH63UOE          潮香饼屋  餐饮服务;餐饮相关场所;餐饮相关    13631015977;13435597205   \n",
       "22  B0FFH6C3MU           韩宫社  餐饮服务;餐饮相关场所;餐饮相关                15913009260   \n",
       "23  B030000WIV      大卡司(庵埠店)      餐饮服务;冷饮店;冷饮店                13690043210   \n",
       "29  B0FFI9OYSJ        江西瑞金小炒      餐饮服务;中餐厅;中餐厅    13715795016;13715817029   \n",
       "0   B030000E2W         声乐大酒店   住宿服务;宾馆酒店;四星级宾馆  0768-6669338;0768-5829338   \n",
       "16  B03000MU8U          鸿达住宿  住宿服务;旅馆招待所;旅馆招待所   0768-6670066;13531524235   \n",
       "\n",
       "   direction distance              location              address poiweight  \\\n",
       "9         东北  86.0521  116.678737,23.454354              喜乐大厦斜对面  0.341181   \n",
       "20        东南  146.645  116.679004,23.452798  庵埠镇文里村亨利北路文里小学运动场隔壁  0.157045   \n",
       "22        东北  301.582  116.679473,23.456241      庵埠镇安南路中段达标大酒店附近  0.149866   \n",
       "23        东北  213.834  116.679017,23.455568               亨安旅馆附近  0.414814   \n",
       "29        西北  109.673  116.677238,23.454406       亨利路与桑浦街交叉口西50米  0.207743   \n",
       "0          南  86.0879  116.678116,23.453059                 亨利北路  0.511695   \n",
       "16        西南  262.482  116.676815,23.451795      侨文路与安南路交叉口南100米  0.254024   \n",
       "\n",
       "   businessarea  \n",
       "9            []  \n",
       "20           []  \n",
       "22           []  \n",
       "23           []  \n",
       "29           []  \n",
       "0            []  \n",
       "16           []  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "休息场所_df = pd.concat([df_餐饮服务, df_住宿服务], axis=0)\n",
    "休息场所_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <td>0</td>\n",
       "      <td>3516255622</td>\n",
       "      <td>050100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.709741,23.547565</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
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       "      <td>[]</td>\n",
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       "      <td>0</td>\n",
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       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
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       "      <td>050100</td>\n",
       "      <td>...</td>\n",
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       "      <td>[]</td>\n",
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       "      <td>[]</td>\n",
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       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
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       "      <td>050100</td>\n",
       "      <td>...</td>\n",
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       "      <td>[]</td>\n",
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       "    <tr>\n",
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       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>住宿服务;宾馆酒店;宾馆酒店</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516379212</td>\n",
       "      <td>100100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.911317,23.662589</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516376012</td>\n",
       "      <td>050100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.887090,23.637420</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;四川菜(川菜)</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516345622</td>\n",
       "      <td>050102</td>\n",
       "      <td>...</td>\n",
       "      <td>116.586244,23.631353</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>4.3</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;餐饮相关场所;餐饮相关</td>\n",
       "      <td>[{'title': '门头照', 'url': 'http://store.is.auto...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516346600</td>\n",
       "      <td>050000</td>\n",
       "      <td>...</td>\n",
       "      <td>116.576782,23.634344</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>3.3</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>住宿服务;宾馆酒店;四星级宾馆</td>\n",
       "      <td>[{'title': 'Logo', 'url': 'http://store.is.aut...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516154410</td>\n",
       "      <td>100103</td>\n",
       "      <td>...</td>\n",
       "      <td>116.678116,23.453059</td>\n",
       "      <td>[]</td>\n",
       "      <td>F50F007022_406</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>3.5</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>住宿服务;宾馆酒店;四星级宾馆</td>\n",
       "      <td>[{'title': 'Logo', 'url': 'http://store.is.aut...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516155412</td>\n",
       "      <td>100103</td>\n",
       "      <td>...</td>\n",
       "      <td>116.685429,23.462289</td>\n",
       "      <td>[]</td>\n",
       "      <td>F50F007022_885</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>4.3</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>B030000DS3</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;餐饮相关场所;餐饮相关</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516348910</td>\n",
       "      <td>050000</td>\n",
       "      <td>...</td>\n",
       "      <td>116.614246,23.655271</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>78.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>3516348720</td>\n",
       "      <td>050100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.588515,23.655882</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>住宿服务;宾馆酒店;宾馆酒店</td>\n",
       "      <td>[{'title': 'Logo', 'url': 'http://store.is.aut...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516440911</td>\n",
       "      <td>100100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.619599,23.670989</td>\n",
       "      <td>[]</td>\n",
       "      <td>F50F004021_1666</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>3.9</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>B0FFG5MQA1</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;东北菜</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516359402</td>\n",
       "      <td>050113</td>\n",
       "      <td>...</td>\n",
       "      <td>116.685833,23.660238</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>70.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>[{'title': '糕烧粉葛芋', 'url': 'http://store.is.au...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516354100</td>\n",
       "      <td>050100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.641440,23.617461</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>3.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;火锅店</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516359000</td>\n",
       "      <td>050117</td>\n",
       "      <td>...</td>\n",
       "      <td>116.625365,23.660527</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>128.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516470802</td>\n",
       "      <td>050100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.986296,23.669124</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>71.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>440000</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>餐饮服务;中餐厅;中餐厅</td>\n",
       "      <td>[{'title': [], 'url': 'http://store.is.autonav...</td>\n",
       "      <td>0</td>\n",
       "      <td>3516359011</td>\n",
       "      <td>050100</td>\n",
       "      <td>...</td>\n",
       "      <td>116.631740,23.663749</td>\n",
       "      <td>[]</td>\n",
       "      <td>F50F005022_12894</td>\n",
       "      <td>0</td>\n",
       "      <td>11.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        parent distance   pcode importance recommend               type  \\\n",
       "0           []       []  440000         []         0  住宿服务;宾馆酒店;经济型连锁酒店   \n",
       "1           []       []  440000         []         0   餐饮服务;餐饮相关场所;餐饮相关   \n",
       "2           []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "3           []       []  440000         []         0   餐饮服务;餐饮相关场所;餐饮相关   \n",
       "4           []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "5           []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "6           []       []  440000         []         0     住宿服务;宾馆酒店;宾馆酒店   \n",
       "7           []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "8           []       []  440000         []         0   餐饮服务;中餐厅;四川菜(川菜)   \n",
       "9           []       []  440000         []         0   餐饮服务;餐饮相关场所;餐饮相关   \n",
       "10          []       []  440000         []         0    住宿服务;宾馆酒店;四星级宾馆   \n",
       "11          []       []  440000         []         0    住宿服务;宾馆酒店;四星级宾馆   \n",
       "12  B030000DS3       []  440000         []         0   餐饮服务;餐饮相关场所;餐饮相关   \n",
       "13          []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "14          []       []  440000         []         0     住宿服务;宾馆酒店;宾馆酒店   \n",
       "15  B0FFG5MQA1       []  440000         []         0       餐饮服务;中餐厅;东北菜   \n",
       "16          []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "17          []       []  440000         []         0       餐饮服务;中餐厅;火锅店   \n",
       "18          []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "19          []       []  440000         []         0       餐饮服务;中餐厅;中餐厅   \n",
       "\n",
       "                                               photos discount_num  \\\n",
       "0   [{'title': 'Logo', 'url': 'http://store.is.aut...            0   \n",
       "1   [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "2                                                  []            0   \n",
       "3                                                  []            0   \n",
       "4   [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "5   [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "6   [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "7   [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "8   [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "9   [{'title': '门头照', 'url': 'http://store.is.auto...            0   \n",
       "10  [{'title': 'Logo', 'url': 'http://store.is.aut...            0   \n",
       "11  [{'title': 'Logo', 'url': 'http://store.is.aut...            0   \n",
       "12  [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "13                                                 []            0   \n",
       "14  [{'title': 'Logo', 'url': 'http://store.is.aut...            0   \n",
       "15  [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "16  [{'title': '糕烧粉葛芋', 'url': 'http://store.is.au...            0   \n",
       "17  [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "18  [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "19  [{'title': [], 'url': 'http://store.is.autonav...            0   \n",
       "\n",
       "      gridcode typecode  ...              location shopid        navi_poiid  \\\n",
       "0   3516359001   100105  ...  116.631295,23.660176     []   F50F005022_7159   \n",
       "1   3516359122   050000  ...  116.648312,23.664124     []                []   \n",
       "2   3516255622   050100  ...  116.709741,23.547565     []                []   \n",
       "3   3516346922   050000  ...  116.621204,23.641399     []                []   \n",
       "4   3516359112   050100  ...  116.649598,23.662181     []   F50F005022_8488   \n",
       "5   3516156411   050100  ...  116.679469,23.470144     []  F50F007022_29132   \n",
       "6   3516379212   100100  ...  116.911317,23.662589     []                []   \n",
       "7   3516376012   050100  ...  116.887090,23.637420     []    F50F005024_310   \n",
       "8   3516345622   050102  ...  116.586244,23.631353     []                []   \n",
       "9   3516346600   050000  ...  116.576782,23.634344     []                []   \n",
       "10  3516154410   100103  ...  116.678116,23.453059     []    F50F007022_406   \n",
       "11  3516155412   100103  ...  116.685429,23.462289     []    F50F007022_885   \n",
       "12  3516348910   050000  ...  116.614246,23.655271     []                []   \n",
       "13  3516348720   050100  ...  116.588515,23.655882     []                []   \n",
       "14  3516440911   100100  ...  116.619599,23.670989     []   F50F004021_1666   \n",
       "15  3516359402   050113  ...  116.685833,23.660238     []                []   \n",
       "16  3516354100   050100  ...  116.641440,23.617461     []                []   \n",
       "17  3516359000   050117  ...  116.625365,23.660527     []                []   \n",
       "18  3516470802   050100  ...  116.986296,23.669124     []                []   \n",
       "19  3516359011   050100  ...  116.631740,23.663749     []  F50F005022_12894   \n",
       "\n",
       "   groupbuy_num biz_ext.cost biz_ext.rating indoor_data.truefloor  \\\n",
       "0             0           []            4.5                    []   \n",
       "1             0        66.00            3.5                    []   \n",
       "2             0           []             []                    []   \n",
       "3             0           []             []                    []   \n",
       "4             0        69.00            3.0                    []   \n",
       "5             0        63.00            3.5                    []   \n",
       "6             0           []             []                    []   \n",
       "7             0           []             []                    []   \n",
       "8             0           []            4.3                    []   \n",
       "9             0           []            3.3                    []   \n",
       "10            0           []            3.5                    []   \n",
       "11            0           []            4.3                    []   \n",
       "12            0        78.00            4.0                    []   \n",
       "13            0           []            3.0                    []   \n",
       "14            0           []            3.9                    []   \n",
       "15            0        70.00            4.0                    []   \n",
       "16            0           []            3.0                    []   \n",
       "17            0       128.00            3.0                    []   \n",
       "18            0        71.00            3.5                    []   \n",
       "19            0        11.00            3.5                    []   \n",
       "\n",
       "   indoor_data.cpid indoor_data.floor biz_ext.meal_ordering  \n",
       "0                []                []                   NaN  \n",
       "1                []                []                     0  \n",
       "2                []                []                     0  \n",
       "3                []                []                     0  \n",
       "4                []                []                     0  \n",
       "5                []                []                     0  \n",
       "6                []                []                   NaN  \n",
       "7                []                []                     0  \n",
       "8                []                []                     0  \n",
       "9                []                []                     0  \n",
       "10               []                []                   NaN  \n",
       "11               []                []                   NaN  \n",
       "12               []                []                     0  \n",
       "13               []                []                     0  \n",
       "14               []                []                   NaN  \n",
       "15               []                []                     0  \n",
       "16               []                []                     0  \n",
       "17               []                []                     0  \n",
       "18               []                []                     0  \n",
       "19               []                []                     0  \n",
       "\n",
       "[20 rows x 46 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def place_text(keywords,types=None,city=None,citylimit=None,children=None,page=None,extensions='all',sig=None)->dict:\n",
    "    \"\"\"获取逆地理编码\"\"\"\n",
    "    url = 'https://restapi.amap.com/v3/place/text?parameters'\n",
    "    params={\n",
    "        'key':key,\n",
    "        'keywords':keywords,\n",
    "        'types':types,\n",
    "        'city':city,\n",
    "        'citylimit':citylimit,\n",
    "        'children':children,\n",
    "        'page':page,\n",
    "        'extensions':extensions,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()\n",
    "    return data\n",
    "休息场所 = place_text('美食|酒店',city='潮州市',page=1,children=1)\n",
    "display(json_normalize(休息场所[\"pois\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'suggestion': {'keywords': [], 'cities': []},\n",
       " 'count': '884',\n",
       " 'infocode': '10000',\n",
       " 'pois': [{'parent': [],\n",
       "   'distance': [],\n",
       "   'pcode': '440000',\n",
       "   'importance': [],\n",
       "   'biz_ext': {'cost': [], 'rating': '4.5'},\n",
       "   'recommend': '0',\n",
       "   'type': '住宿服务;宾馆酒店;经济型连锁酒店',\n",
       "   'photos': [{'title': 'Logo',\n",
       "     'url': 'http://store.is.autonavi.com/showpic/ea149abaa350591f17e1b6e21a6c6b48'},\n",
       "    {'title': '客房',\n",
       "     'url': 'http://store.is.autonavi.com/showpic/9c3d89cfcb78c1bba57301e54142a7ba'},\n",
       "    {'title': [],\n",
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       "   'type': '餐饮服务;中餐厅;火锅店',\n",
       "   'photos': [{'title': [],\n",
       "     'url': 'http://store.is.autonavi.com/showpic/6a126292228a9abef86c0f2a39051f26'},\n",
       "    {'title': '环境',\n",
       "     'url': 'http://store.is.autonavi.com/showpic/0e178c21652195dd9c9085b87eb556f3'},\n",
       "    {'title': '菜品',\n",
       "     'url': 'http://store.is.autonavi.com/showpic/2507ed3a0d578d6bd9434f4d2878e821'}],\n",
       "   'discount_num': '0',\n",
       "   'gridcode': '3516359000',\n",
       "   'typecode': '050117',\n",
       "   'shopinfo': '0',\n",
       "   'poiweight': [],\n",
       "   'citycode': '0768',\n",
       "   'adname': '湘桥区',\n",
       "   'children': [],\n",
       "   'alias': [],\n",
       "   'tel': '0768-2990600',\n",
       "   'id': 'B0FFIOBFZU',\n",
       "   'tag': '极品鲜毛肚,现炸酥肉,玫瑰圆子,极品鲜鹅肠,红糖糍粑',\n",
       "   'event': [],\n",
       "   'entr_location': '116.625678,23.660682',\n",
       "   'indoor_map': '0',\n",
       "   'email': [],\n",
       "   'timestamp': '2020-07-09 03:53:11',\n",
       "   'website': [],\n",
       "   'address': '蓝玥湾酒店旁',\n",
       "   'adcode': '445102',\n",
       "   'pname': '广东省',\n",
       "   'biz_type': 'diner',\n",
       "   'cityname': '潮州市',\n",
       "   'postcode': [],\n",
       "   'match': '0',\n",
       "   'indoor_data': {'truefloor': [], 'cpid': [], 'floor': []},\n",
       "   'business_area': [],\n",
       "   'childtype': [],\n",
       "   'exit_location': [],\n",
       "   'name': '小龙坎老火锅(口岸店)',\n",
       "   'location': '116.625365,23.660527',\n",
       "   'shopid': [],\n",
       "   'navi_poiid': [],\n",
       "   'groupbuy_num': '0'},\n",
       "  {'parent': [],\n",
       "   'distance': [],\n",
       "   'pcode': '440000',\n",
       "   'importance': [],\n",
       "   'biz_ext': {'cost': '71.00', 'rating': '3.5', 'meal_ordering': '0'},\n",
       "   'recommend': '0',\n",
       "   'type': '餐饮服务;中餐厅;中餐厅',\n",
       "   'photos': [{'title': [],\n",
       "     'url': 'http://store.is.autonavi.com/showpic/fb2b5c190718e9563d29fff35378dbed'},\n",
       "    {'title': [],\n",
       "     'url': 'http://store.is.autonavi.com/showpic/72de32f2619d734bc135f552399120f1'},\n",
       "    {'title': [],\n",
       "     'url': 'http://store.is.autonavi.com/showpic/68e66a73353e8690358106242db654b3'}],\n",
       "   'discount_num': '0',\n",
       "   'gridcode': '3516470802',\n",
       "   'typecode': '050100',\n",
       "   'shopinfo': '0',\n",
       "   'poiweight': [],\n",
       "   'citycode': '0768',\n",
       "   'adname': '饶平县',\n",
       "   'children': [],\n",
       "   'alias': [],\n",
       "   'tel': '0768-8868766',\n",
       "   'id': 'B0FFITHMSG',\n",
       "   'tag': '钢管鸡,酸汤肥牛,凤爪,虾饺,荔浦芋头,农家猪肉肠粉,黑金流沙包,红米脆皮肠,一品油条,笼珠点心,孖宝双拼烧卖,荷叶贵妃鸡,扬州炒饭,xo萝卜糕,三味珍宝,青菜,乳鸽,广式葱油饼',\n",
       "   'event': [],\n",
       "   'entr_location': [],\n",
       "   'indoor_map': '0',\n",
       "   'email': [],\n",
       "   'timestamp': '2020-06-21 23:16:14',\n",
       "   'website': [],\n",
       "   'address': '饶平大道23号开来酒店旁',\n",
       "   'adcode': '445122',\n",
       "   'pname': '广东省',\n",
       "   'biz_type': 'diner',\n",
       "   'cityname': '潮州市',\n",
       "   'postcode': [],\n",
       "   'match': '0',\n",
       "   'indoor_data': {'truefloor': [], 'cpid': [], 'floor': []},\n",
       "   'business_area': [],\n",
       "   'childtype': [],\n",
       "   'exit_location': [],\n",
       "   'name': '阅点点心世家',\n",
       "   'location': '116.986296,23.669124',\n",
       "   'shopid': [],\n",
       "   'navi_poiid': [],\n",
       "   'groupbuy_num': '0'},\n",
       "  {'parent': [],\n",
       "   'distance': [],\n",
       "   'pcode': '440000',\n",
       "   'importance': [],\n",
       "   'biz_ext': {'cost': '11.00', 'rating': '3.5', 'meal_ordering': '0'},\n",
       "   'recommend': '0',\n",
       "   'type': '餐饮服务;中餐厅;中餐厅',\n",
       "   'photos': [{'title': [],\n",
       "     'url': 'http://store.is.autonavi.com/showpic/568b6f1aa310f9ed880d8fc2'},\n",
       "    {'title': '猪肉蛋肠粉',\n",
       "     'url': 'http://store.is.autonavi.com/showpic/49ff5c87c2dc89c804cfaa318900316e'},\n",
       "    {'title': [],\n",
       "     'url': 'http://store.is.autonavi.com/showpic/774fd6eb91af367180c1b7736a96f24b'}],\n",
       "   'discount_num': '0',\n",
       "   'gridcode': '3516359011',\n",
       "   'typecode': '050100',\n",
       "   'shopinfo': '0',\n",
       "   'poiweight': [],\n",
       "   'citycode': '0768',\n",
       "   'adname': '湘桥区',\n",
       "   'children': [],\n",
       "   'alias': [],\n",
       "   'tel': '13631022233',\n",
       "   'id': 'B0FFG4LZQN',\n",
       "   'tag': '金针菇肠粉,牛肉肠粉,猪肉蛋肠粉,猪肉冬笋肠粉',\n",
       "   'event': [],\n",
       "   'entr_location': [],\n",
       "   'indoor_map': '0',\n",
       "   'email': [],\n",
       "   'timestamp': '2020-06-19 20:06:35',\n",
       "   'website': [],\n",
       "   'address': '潮枫路云和酒店首层铺面',\n",
       "   'adcode': '445102',\n",
       "   'pname': '广东省',\n",
       "   'biz_type': 'diner',\n",
       "   'cityname': '潮州市',\n",
       "   'postcode': [],\n",
       "   'match': '0',\n",
       "   'indoor_data': {'truefloor': [], 'cpid': [], 'floor': []},\n",
       "   'business_area': [],\n",
       "   'childtype': [],\n",
       "   'exit_location': [],\n",
       "   'name': '我家肠粉&炖盅&蒸面',\n",
       "   'location': '116.631740,23.663749',\n",
       "   'shopid': [],\n",
       "   'navi_poiid': 'F50F005022_12894',\n",
       "   'groupbuy_num': '0'}],\n",
       " 'status': '1',\n",
       " 'info': 'OK'}"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "休息场所"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pandas.io.json import json_normalize\n",
    "\n",
    "import requests\n",
    "key =\"9**************\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def driving(origin,destination,sig=None)->dict:\n",
    "    url = 'https://restapi.amap.com/v3/direction/driving?parameters'\n",
    "    params={\n",
    "        'key':key,\n",
    "        'origin':origin,\n",
    "        'destination':destination,\n",
    "        'output':'json'\n",
    "    }\n",
    "    response = requests.get(url,params=params)\n",
    "    data = response.json()['route']['paths'][0]['steps']\n",
    "    data_df = json_normalize(data)\n",
    "    return data_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instruction</th>\n",
       "      <th>orientation</th>\n",
       "      <th>road</th>\n",
       "      <th>distance</th>\n",
       "      <th>tolls</th>\n",
       "      <th>toll_distance</th>\n",
       "      <th>toll_road</th>\n",
       "      <th>duration</th>\n",
       "      <th>polyline</th>\n",
       "      <th>action</th>\n",
       "      <th>assistant_action</th>\n",
       "      <th>tmcs</th>\n",
       "      <th>cities</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>沿安南路向西南行驶194米左转调头</td>\n",
       "      <td>西南</td>\n",
       "      <td>安南路</td>\n",
       "      <td>194</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>60</td>\n",
       "      <td>116.67809,23.453845;116.676975,23.452431</td>\n",
       "      <td>左转调头</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{'lcode': [], 'distance': '194', 'status': '畅...</td>\n",
       "      <td>[{'name': '潮州市', 'citycode': '0768', 'adcode':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>沿安南路向东北行驶574米左转调头</td>\n",
       "      <td>东北</td>\n",
       "      <td>安南路</td>\n",
       "      <td>574</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>106</td>\n",
       "      <td>116.677023,23.452391;116.677834,23.453433;116....</td>\n",
       "      <td>左转调头</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{'lcode': [], 'distance': '142', 'status': '畅...</td>\n",
       "      <td>[{'name': '潮州市', 'citycode': '0768', 'adcode':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>沿安南路向西南行驶151米右转</td>\n",
       "      <td>西南</td>\n",
       "      <td>安南路</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>26</td>\n",
       "      <td>116.680087,23.456766;116.6798,23.45635;116.679...</td>\n",
       "      <td>右转</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{'lcode': [], 'distance': '54', 'status': '畅通...</td>\n",
       "      <td>[{'name': '潮州市', 'citycode': '0768', 'adcode':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>沿韩江街向西北行驶19米到达目的地</td>\n",
       "      <td>西北</td>\n",
       "      <td>韩江街</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>9</td>\n",
       "      <td>116.679293,23.455603;116.679149,23.455712</td>\n",
       "      <td>[]</td>\n",
       "      <td>到达目的地</td>\n",
       "      <td>[{'lcode': [], 'distance': '19', 'status': '未知...</td>\n",
       "      <td>[{'name': '潮州市', 'citycode': '0768', 'adcode':...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         instruction orientation road distance tolls toll_distance toll_road  \\\n",
       "0  沿安南路向西南行驶194米左转调头          西南  安南路      194     0             0        []   \n",
       "1  沿安南路向东北行驶574米左转调头          东北  安南路      574     0             0        []   \n",
       "2    沿安南路向西南行驶151米右转          西南  安南路      151     0             0        []   \n",
       "3  沿韩江街向西北行驶19米到达目的地          西北  韩江街       19     0             0        []   \n",
       "\n",
       "  duration                                           polyline action  \\\n",
       "0       60           116.67809,23.453845;116.676975,23.452431   左转调头   \n",
       "1      106  116.677023,23.452391;116.677834,23.453433;116....   左转调头   \n",
       "2       26  116.680087,23.456766;116.6798,23.45635;116.679...     右转   \n",
       "3        9          116.679293,23.455603;116.679149,23.455712     []   \n",
       "\n",
       "  assistant_action                                               tmcs  \\\n",
       "0               []  [{'lcode': [], 'distance': '194', 'status': '畅...   \n",
       "1               []  [{'lcode': [], 'distance': '142', 'status': '畅...   \n",
       "2               []  [{'lcode': [], 'distance': '54', 'status': '畅通...   \n",
       "3            到达目的地  [{'lcode': [], 'distance': '19', 'status': '未知...   \n",
       "\n",
       "                                              cities  \n",
       "0  [{'name': '潮州市', 'citycode': '0768', 'adcode':...  \n",
       "1  [{'name': '潮州市', 'citycode': '0768', 'adcode':...  \n",
       "2  [{'name': '潮州市', 'citycode': '0768', 'adcode':...  \n",
       "3  [{'name': '潮州市', 'citycode': '0768', 'adcode':...  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "我_大卡司 = driving('116.678113,23.453833','116.679017,23.455568')\n",
    "我_大卡司"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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